Daily Environments During Emerging Adulthood and Gender Atypical Occupational Choices: The Role of Sexist Experiences

Abstract

Past research on occupational choices often focuses on the role of personal attributes. Research is needed that examines whether daily environments and individuals’ reactivity to these environments contribute to occupational choices. This study utilizes experience sampling methodology to examine whether daily sexism and affective reactivity to sexism predict the gender typicality of desired occupations of emerging adults in male-dominated majors (MDMs). 40 women and 40 men college students in MDMs reported desired occupations and experiences of sexism and general mood during the past hour four times a day for 2 weeks – allowing for an examination of whether some individuals report a more negative mood when they recently experienced sexism (i.e., reactivity). Results indicated that higher reactivity to sexism (but not daily sexism) predicted women desiring more female-typed and men desiring more male-typed occupations. Results suggest that career counselors should consider the role of daily sexism in career development.

Keywords

career aspirations women in male-dominated fields gender typicality sexism reactivity

Although women make up roughly 47% of the workforce in the U.S. (American Association of University Women [AAUW], 2018), as of 2019 only 7.1% of women work in male-dominated fields such as computer science and construction (Institute for Women’s Policy Research [IWPR], 2020). This is problematic for a number of reasons at the society-level, including the fact that it contributes to the gender wage gap (Hegewisch, 2018) and lack of diversity may stifle creativity, innovation, and performance in male-dominated fields (Lambert, 2016). At the individual-level, it may prevent individuals from choosing occupations they may enjoy and be successful in while earning high wages.

Although low rates of women in male-dominated fields are a product of experiences throughout one’s life – from childhood to adulthood (Hill et al., 2010) – emerging adulthood plays a particularly important role in individuals’ occupational choices. Emerging adults (EAs) are exploring possible occupational choices and identity issues related to work (e.g., Will I be able to get hired in this occupation? Will I fit in at work?) and laying the foundations for adult work lives (Arnett, 2000). As a result of experiences during emerging adulthood, changes in desired occupational choices are common, but particularly for women exploring career options in male-dominated fields. In fact, women earning a degree in a male-dominated major (MDM), such as STEM fields like computer science, are more likely than their male peers to pursue a career in non-male dominated fields after graduation (Shaw & Stanton, 2012; Xu, 2017).

During emerging adulthood, women in male-dominated fields are often subjected to sex-based discrimination and harassment, which may contribute to women’s decisions to leave these fields (Cohoon et al., 2009). The purpose of the present study was to examine whether daily experiences during emerging adulthood – namely sexism and affective reactivity to sexism – predict the gender typicality of the desired occupations of men and women in MDMs.

Sexism and Gender Typicality of Occupational Choices

Social Cognitive Career Theory (SCCT) refers to the bidirectional associations between personal attributes (e.g., self-efficacy, expectation of positive outcome), external environmental factors (e.g., exposure and opportunities to career-relevant activities and education, level of support and barriers), and overt behaviors (e.g., practicing, training, or enrolling in a particular academic major) to influence career development (Lent et al., 1994). Those who have high perceived self-efficacy, positive outcome expectations, and relevant opportunities for exposure to career activities are more likely to sustain motivation and career development behaviors.

Moreover, the choice model of SCCT suggests career development involves the intercorrelations between 1) career interests, which are preceded by self-efficacy and outcome expectations and result in career goals, 2) career choice (i.e., implementing actions in pursuit of career goals), and 3) performance (e.g., successes and failures) which creates feedback loops and shapes future career behavior. Individuals develop career goals based on career interests they believe they have sufficient efficacy to pursue and achieve, and they hold positive expectations of success or reward in the attainment of their career goals. Then, individuals implement career choice behaviors such as enrolling for an academic major or training program and utilizing self-regulation strategies in pursuit of their career goals. Finally, the individual reevaluates future career goals and career choice actions based on the feedback they received from their performance or consequences of their career choice actions. This model posits that supportive environments are essential to positive career development, and some environmental factors and barriers may constrain career development. Additionally, this model posits that under less supportive environments, career interest may need to be compromised in favor of more pragmatic, urgent, or culturally accepted occupations.

The tenants of SCCT suggest that sexism, defined as gender-specific stressors that occur to an individual due to their gender (Klonoff & Landrine, 1995), may play a role in occupational choices. Sexism includes behaviors and verbal comments, and can be overt (e.g., unwanted sexual attention or harassment) or subtle (e.g., being treated differently due to gender). SCCT suggests that EAs who repeatedly experience or observe same-gender targeted sexism (i.e., women observing sexism targeted at women and men observing sexism targeted at men) related to work competence and abilities may feel the need to reevaluate their career goals and compromise their true occupational interests for a culturally accepted, gender-typical or gender-neutral field.

Research on EAs’ occupational choices – including women’s pursuit of male-dominated fields – often focuses on the role of the personal attributes component of SCCT model as opposed to environmental influences (Duffy & Dik, 2009). For example, research finds that individuals with more sexist attitudes are less likely to pursue gender atypical occupations (e.g., Leaper & Van, 2008). Less research has focused on environmental contributors to EAs’ occupational choices such as experiences of sexism. Women in STEM occupations report a more negative workplace climate compared to men (Riffle et al., 2013), and graduate and undergraduate women in male-dominated fields commonly report experiencing sexism (Barthelemy et al., 2016; Erwin and Maurutto, 1998; MacLachlan, 2006), frequent exclusion, stereotyping and harassment (DeWelde & Laursen, 2011), microaggressions (Cabay, et al., 2018), and many other negative incidents (Cabay et al., 2018).

In line with the proposition of SCCT that less supportive environments may discourage individuals’ pursuit of gender atypical careers, there is evidence that sexist environments may play a role in women’s attrition from male-dominated doctoral programs. Specifically, a 2009 study examining the role of sexism in women’s persistence in computer science and computer science engineering (CSE) programs found that about 7% of women in the program who thought of leaving cited sexism as the source of their turnover intentions. Further, about 38% of the women who left the program cited sexism as the cause (Cohoon et al., 2009). Moreover, the results of this study suggest that the odds of women dropping out of the STEM program were over 20 times greater for women who thought of leaving due to experienced or observed sexism, compared to women who thought of leaving for reasons other than sexism. The negative implications of sexist environments for women’s career development extends to the workplace in that young and middle-aged adult professional women’s experiences of workplace sexism in male-dominated fields is associated with lower levels of job satisfaction (Riffle et al., 2013; Rubin et al., 2019), sense of belonging (Rubin et al., 2019), and work performance (Torre, 2014), along with higher rates of turnover intentions (Riffle et al., 2013).

Little research has examined the role of male-targeted sexism in male-dominated fields, and even less has examined the role of male-targeted sexism in men’s career interests and choices among male EAs pursing male-dominated fields. Research, however, finds that male college students commonly report experiencing sexism (Hill & Silva, 2005) and that men in MDMs experience similar rates of daily sexism when engaging in major-related activities, compared to women in MDMs (Lawson, 2020). The purpose of the present study was to examine the role of sexist experiences in the desired occupations of men and women in MDMs.

Affective Reactivity to Sexism and Gender Typicality of Occupational Choices

To fully understand the role of sexist experiences in the desired occupations of EAs enrolled in MDMs, much of the stress literature and theoretical models argue that research should take into account both the experience of sexism and reactivity to sexism – or the probability that an individual will react to the stressor emotionally or physically (Bolger & Zuckerman, 1995). Stressors, such as sexism, do not have the same implications for everyone: two individuals can experience the same sexist event, yet react very differently.

Similar to SCCT, the Transactional Model of Stress (TMS; Lazarus & Folkman, 1984) takes a social-cognitive approach and emphasizes how both the environment and an individual’s cognitive appraisal of the environment has implications for personal attributes (such as mood) and overt behaviors, such as persistence in the face of obstacles. According to TMS, when an individual experiences a stressful event, such as sexism, they first examine the stressfulness of the situation by utilizing two appraisal processes. During the primary appraisal process, individuals determine whether or not the stressful event is relevant to themselves (i.e., if the stressful event poses a threat). The secondary appraisal process consists of the individual determining whether they have the resources to cope with the stressor. If the stressor poses a threat, but the individual does not have the resources to cope with the threat, this results in a stress response, or reactivity. As such, according to this model, the exposure to the stressor in addition to how one reacts to the stressor can have implications for one’s well-being.

Given that TMS (Lazarus & Folkman, 1984) asserts that an individual must appraise a stressful event as relevant to themselves and then determine that they do not have the necessary resources to cope with the stressful event in order to cause distress, the implications of stressful events such as sexism can vary from person to person. In fact, research has found that women in MDMs are more reactive to daily sexist events, compared to men in MDMs and women in gender-neutral majors (GNMs) (Lawson, 2020). One reason for this may be related to gender stereotypes. Given the stereotypes that women are less skilled in areas that are typically associated with male-dominated fields such as math (Gunderson et al., 2011), women in MDMs may be more likely to perceive sexism as a threat and experience reactivity. Ultimately, sexism and reactivity may hurt women EAs’ achievement and alter career decisions more so than their male peers in MDMs. In fact, Schuster and Martiny (2017) found that the presence of gender-related stereotypes can influence EA women’s STEM career aspirations. More specifically, when women were presented with a stereotype-activating scenario they anticipated experiencing more negative and less positive affect as well as a heightened sense of threat. This lowered anticipated positive affect was found to indirectly lower women’s STEM career aspirations; however, the stereotype-activating scenario had no effect on men’s anticipated affect or their STEM career aspirations (Schuster & Martiny, 2017).

In addition, women in MDMs may be more likely to feel they do not have the resources available to cope with the threat, relative to their male peers. For instance, past research has found that women in MDMs are less likely to have power and have fewer overall resources compared to their male counterparts (Eagly & Wood, 2012; Blickenstaff, 2005). Additionally, women in MDMs also report lower levels of perceived social support and socioemotional mentoring compared to their male counterparts (Robnett et al., 2019; Stout et al., 2013). This, in turn, can further exasperate women’s feelings of decreased social belonging and loneliness within their major (Hopmeyer et al., 2020). This can lead to women feeling as though they do not have the necessary resources (e.g., social support and social belongingness) to deal with the threat (e.g., sexism) which can then lead to distress, or reactivity.

No known research to the authors knowledge has examined the role of reactivity to daily sexism in EAs’ occupational choices. By filling this void, we are considering the dynamic nature of both personal attributes and the environment – consistent with both SCCT and TMS – and considering how the cognitive appraisal process of gender-related environmental stressors (e.g.., sexism) may have implications for the persistence in gender atypical occupations among individuals enrolled in MDMs.

The Present Study

Experience sampling methodology (ESM) is a longitudinal research methodology that involves signaling participants to report on their current experiences at multiple time points. For example, participants may be signaled to complete a survey multiple times a day about their experiences in the previous hour. Strengths of this methodology include the fact that ESM increases ecological validity (generalizability to real-life situations) and reduces memory recall distortions, given participants recall their experiences over shorter intervals of time. In addition, ESM may be particularly useful when studying women in nontraditional fields in that it captures the daily experiences of subtle and explicit day-to-day experiences of sexism and the impact it has on the psychological well-being and sense of belonging of participants (London., Rosenthal, & Gonzalez, 2011).

A majority of past research only examines overall levels of sexism (e.g., how often in your career have you experienced sexism) in relation to occupational choices. Research is needed, however, that considers the role of reactivity to daily sexism – which requires the use of ESM. The present study extends past research by utilizing ESM methodology and having women and men college students in MDMs report experiences of sexism and general mood during the past hour on four separate occasions throughout the day for 2 weeks – allowing for an examination of whether some individuals are more likely to report a more negative general mood during the hour in which they experienced sexism. Using these ESM reports, the present study examines whether daily sexism and affective reactivity to sexism predict the gender typicality of desired occupations among EAs.

SCCT ( Lent et al., 1994 ) asserts that non-supportive environments and personal attributes such as lower expectations for positive career outcomes may deter individuals from pursuing a previously desired occupation and encourage individuals to pursue a more pragmatic and culturally accepted occupation. Because men in MDMs are already in the culturally accepted field, whereas women are not, it is predicted that:

Hypothesis 1: Experiencing sexism in MDMs will be associated with women students (but not men students) desiring a more gender typical occupation.

Hypothesis 2: Women students in MDMs (but not men students) who are more reactive to sexism will report desiring a more gender typical occupation.

Method

Participants

Participants were from a larger study designed to examine daily experiences of women in MDMs (n = 40), relative to their male peers in MDMs (n = 40) and female peers in GNMs (n = 40; Author Citations). Because this study focused on the career aspirations of students in MDMs, only men and women from these majors were included in the study. MDMs were defined as any major where at least two-thirds of students are men both at the university and nationally. Defining male-dominated fields based on whether women are numerical minorities is commonly done in past research (e.g., Frome et al., 2006; Lawson et al., 2018b; Mastekaasa & Smeby, 2008). The most common MDMs among participants included computer science and finance (see Table 1 for a full listing of majors and participant demographics). Participants included 80 students from a midsize, U.S. Midwestern university, ranged from first-year students to seniors in college, and a most participants (66, 82.50%) identified as White.

Table 1.

Participants’ Demographics.

	Total Sample (n = 120)	Women in MDMs (n = 40)	Men in MDMs (n = 40)
	n (%)	n (%)	n (%)
Year in school
First-year	15 (18.75)	4 (10.00)	11 (27.50)
Sophomore	18 (22.50)	7 (17.50)	11 (27.50)
Junior	26 (32.50)	17 (42.50)	9 (22.50)
Senior	21 (26.25)	12 (30.00)	9 (22.50)
Race/Ethnicity
White	66 (82.50)	29 (72.50)	37 (92.50)
Black	7 (8.75)	7 (17.50)	0
Hispanic	3 (3.75)	2 (5.00)	1 (2.50)
Asian	1 (1.25)	1 (2.50)	0
Mixed race	2 (2.50)	1 (2.50)	1 (2.50)
Other	1 (1.25)	0	1 (2.50)
Male-dominated majors
Computer information systems	8 (10.00)	3 (7.50)	5 (12.50)
Computer science	20 (25.00)	8 (20.00)	12 (30.00)
Computer technology	6 (7.50)	2 (5.00)	4 (10.00)
Construction management	6 (7.50)	2 (5.00)	4 (10.00)
Economics	6 (7.50)	3 (7.50)	3 (7.50)
Finance	20 (25.00)	12 (30.00)	8 (20.00)
Industry and technology	1 (1.25)	1 (2.50)	0
Logistics supply chain management	1 (1.25)	1 (2.50)	0
Music media production	5 (6.25)	2 (5.00)	3 (7.50)
Physics	2 (2.50)	1 (2.50)	1 (2.50)
Sport administration	5 (6.25)	5 (12.50)	0

Note. MDM = Male-Dominated Majors.

Procedure

To recruit participants, emails were sent to women and men in MDMs at the university and through the university’s communication center (which sent out the email to all undergraduate students). In addition, participants were recruited via flyer advertisements and in-class presentations. Prospective participants were told that the study examined the daily experiences of college students, including daily stressors, classroom experiences, positive and negative experiences, departmental contexts, and career aspirations. A total of 16 students who contacted the study coordinator to verify eligibility (at least 18 years old, identify as a female or male and majoring in a MDM or identify as female and majoring in a GNM) did not qualify.

The study coordinator scheduled an in-person data collection assessment for all eligible participants. During this assessment, participants completed (1) the informed consent procedure; (2) a Qualtrics survey with questions about their demographics, career aspirations (used in the present study), and other information not used in the present study (e.g., experiences at the university and in their major, attitudes, and health); and (3) the smartphone registration that would enable them to complete the ESM assessments for the following 2 weeks. Participants were compensated $10 for completing the in-person assessment.

Starting the day after the in-person assessment, participants completed five ESM assessments daily for 2 weeks. Participants were signaled to complete the short surveys via text message sent through SurveySignal (Hofmann & Patel, 2014). The first 4 signals (used in the present study – referred to as hourly signals) asked students to report on their experiences during the previous hour, which included whether or not they experienced sexism, emotions, and attitudes. SurveySignal sent hourly signals at random times within four time frames: 9:00–11:30a.m., 11:30a.m.–2:00p.m.; 2:00–4:30p.m., and 4:30–7:00p.m. It took participants approximately 2–3 minutes to complete the hourly signals. Participants (on average) completed 45.62 (SD = 11.09, range = 4–56) out of 56 hourly signals. Participants completed 5431 out of 6720 hourly signals (80.82%), which is comparable to previous ESM research conducted via SurveySignal (77%; Hofmann & Patel, 2014).

The final, end of day signal occurred at 9:00p.m. This survey asked participants to report on daily experiences that were not captured with the hourly signal as well as a few additional measures not used in the hourly signals or in the present study. For the present study, only hourly signals were used in the analyses because they allow for the examination of immediate reactivity to sexism. Participants who completed over half of the ESM signals were compensated $40 (n = 112, 93.33%), and participants who completed less than half of the signals were compensated $20 (n = 8, 6.67%). The in-person and ESM assessments all took place within the third to 13th week of the 16-week semester in the same academic year. The IRB at the university of the PI approved all study procedures prior to data collection (IRB #1068976).

Measures

Items for all measures described below can be seen in Appendix A.

Sexism

During each hourly ESM assessment, participants were asked to report if they personally experienced or witnessed (yes/no) 14 incidents in their interpersonal relationships (not in the media) during the past hour to either themselves or someone of their gender. These 14 items were from Becker and Swim’s (2011) sexist events checklist – which include both subtle and overt sexist events. Although it is difficult to assess the reliability of daily diary measures, as variables are measured via this method when they are predicted to change over time (Cranford et al., 2006), there is evidence of validity. The researchers created items based off daily diary research where college students described gender-related, prejudiced incidents they viewed toward women during a 2-week time period, and these incidents were associated with women experiencing anger, discomfort, and surprise during the incident (Swim et al., 2001). Only 14 of the 24 items in Becker and Swim’s checklist were included to reduce participants’ load during hourly assessments and some items were less relevant to major-related events. Items were modified so that they applied to women and men. For example, the item “Heard traditional negative beliefs that women were not as able to do things as well as men (e.g., low ability with math, sports, cars, or leadership) was edited to state “Heard traditional negative beliefs that your gender is not as able to do things as well as the other gender (e.g., women’s perceived low ability with math, men’s perceived low verbal ability).”

Reactivity to Sexism

ESM data, where participants reported whether sexism occurred (described above) and general mood during the previous hour 4 times a day for 2 weeks, were used to create the reactivity scores. An item from London, Rosenthal, Levy et al. (2011) research was used to assess general mood: “Overall, how were you feeling in the past hour” (1 = Terrible, 7 = Terrific). The item was modified so that it asked about previous hour, rather than entire day. The item was reverse-coded so that higher scores represented a more negative mood. In this sample, there is evidence that the item is a valid measure of general mood, as the average general mood score for each individual across all ESM assessments was significantly correlated with traditional survey measures: poorer general mood was associated with higher scores on Kessler and colleagues’ (2003) measure of psychological distress, r(80) = .53, p < .001, and Cohen et al. (1983) measure of perceived stress, r(80) = .51, p < .001.

Individual reactivity to sexism scores indicated the difference in negative mood between sexism and non-sexism signals. To create these scores, SAS PROC Mixed was utilized, which uses a multi-level hierarchical model (MLM) to estimate level 1 (within-person), level 2 (between-day), and level 3 variability (between-person). In this model, three sexism variables that indicated level 1 sexism (did participants experience sexism within the previous hour on a given signal, 0 = no, 1 = yes), level 2 sexism (average daily sexism participants reported, centered at the grand mean), and level 3 sexism (the average number of signals participants experienced sexism across the 2 weeks, centered at the grand mean) were entered as predictors of hourly emotion. The intercept and slopes for the analysis were outputted, so that each participant had their own intercept (indicating the negative mood level on non-sexism signals for that individual) and reactivity slope (indicating each individual’s change in negative mood in response to sexism in the previous hour). This approach is commonly used in past stress research to examine stressor reactivity as a predictor of health (Author Citation, Charles et al., 2013; Sliwinski et al., 2009).

Desired Occupation

During the in-person assessment, participants were asked, “What is your desired occupation?” and “What types of tasks would you do in your desired occupation?” Similar to previous research examining the gender typicality of occupational choices (e.g., Lawson et al., 2015, 2018b), the gender typicality of occupations reported were coded based on the percent of females in the occupation using data from the U.S. Census Bureau (Bureau of Labor Statistics, 2019). Two graduate students were trained to code by the PI of the study, who has used this method of coding in previous research. The PI introduced the graduate students in psychology programs to previous literature that used this coding, the Web site containing the data and search function for specific occupations, a general list of all occupation categories from the U.S. Census Bureau, and an excel file coding sheet to make comparisons easier between coders. One graduate student coded all desired occupations, the other graduate student separately coded 10% of the occupations (randomly chosen by the PI using a random number generator), and comparisons were made to assess reliability. The coders agreed 83.3% of the time, and all discrepancies were discussed until the coders reached agreement. Men’s scores were reverse-coded so that higher scores were indicative of more gender typical occupations for both men and women. For example, in the U.S., 19.3% of software engineers are male. Thus, women desiring this career would be coded 19.3% and men would be coded 80.7% (100–19.3).

Analyses

General linear models were conducted in SAS to examine the research questions. For research question one, three variables were entered into the model to predict the gender typicality of desired occupations: the average number of signals the person experienced sexism across the 2-week period (grand-mean centered), gender (0 = women, 1 = men), and the interaction between the two variables. This approach allowed us to utilize the ESM assessments to better understand whether the repetitive nature of a “chilly climate” may have implications for desired careers. Participants with missing data were excluded from analyses (4 participants did not report desired occupations).

For research question 2, four variables were entered into the general linear model to predict the gender typicality of desired occupations: the intercept and slope scores from the reactivity MLMs (described above in the reactivity section), gender (0 = women, 1 = men), and the interaction between slope and gender. The intercept indicated participant’s negative emotions during non-sexism signals and the slope indicated an individual’s reactivity to sexism. The inclusion of the slope allowed us to examine whether people who are more immediately reactive to daily sexism (i.e., who were more likely to report negative mood during the same hour that sexism occurred) were more likely to desire gender typical occupations. More missing data occurred for research question 2 because some individuals reported never experiencing sexism (and thus could not experience reactivity to sexism; 17 men and 13 women total). A total of 46 participants were included in analyses for research question 2.

A priori power analyses conducted using G*Power (Faul et al., 2009) indicated that to obtain 95% power for the models with an alpha of .05, a sample size of 74 participants was necessary. For 80% power, a sample size of 43 participants was necessary. Prior to analyses, data were examined for outliers. One male student experienced sexism during more signals than most (over three standard deviations away from the mean). All analyses were conducted with and without the outlier. The conclusions from both sets of analyses, however, were the same. Thus, results are reported from the analyses that kept all data (i.e., did not remove the outlier).

Results

A majority of students experienced sexism at least once across the 2-week period (67.5% of women and 57.5% of men). Men and women did not significantly differ in the percent of hourly signals that they experienced sexism during the 2-week period, t (78) = -.86, p = .39, Cohen’s d = .19. Women experienced sexism during 3.8% of hourly signals, and men experienced sexism during 6.7% of signals. Among individuals who experienced sexism at least once, there were also no gender differences in reactivity to sexism scores, t (48) = -1.15, p = .25, Cohen’s d = .34, men: M = .25, SD = .44, women: M = .10, SD = .43. Not surprisingly, given that men and women from MDMs were recruited for the study, men desired working in more gender typical occupations than women, t (74) = -7.59, p < .001, Cohen’s d = 1.74, men: M = 66.55, SD = 16.29, women: M = 37.73, SD = 16.80. Additional analyses using the non-reverse coded gender typicality scores, with higher scores indicating more female-typed occupations, indicated that women did not desire more female-typed occupations, relative to men, t (74) = -1.13, p = .26, Cohen’s d = .26, men: M = 33.45, SD = 16.29, women: M = 37.73, SD = 16.80.

Sexism and Gender Typicality of Occupational Choices

Results of the regression analysis examining percent of signals participants experienced sexism across the 2-week daily diary time period as a predictor of the gender typicality of desired occupations can be seen in Table 2. Sexism was not a significant predictor of desired occupations among men and women in MDMs, and gender did not moderate this association – failing to support hypothesis 1.

Table 2.

Results of Regression Analyses Examining Sexism as a Predictor of the Gender Typicality of Occupational Choices.

	B	B (SE)
Intercept	0.00	37.93 (2.90)***
Sexism	0.09	15.14 (57.45)
Gender	0.66	28.66 (3.93)***
Gender*Sexism	-0.10	-18.19 (59.75)

Note. Gender (0 = female, 1 = male). Sexism scores represent the percentage of signals participants experienced sexism across the 2-week daily diary period.

*p < .05, **p < .01, ***p < .001.

Affective Reactivity to Sexism and Gender Typicality of Occupational Choices

Affective reactivity to sexism significantly predicted the gender typicality of students’ desired occupations (see Table 3) – even when controlling for general mood on non-sexism days (i.e., between-person differences in daily general mood). More specifically, higher levels of reactivity to sexism were associated with students desiring more gender typical occupations. In other words, women who were more reactive to sexism desired working in more female-typed occupations, and men who were more reactive to sexism desired working in more male-typed occupations. Contrary to the prediction, the interaction between gender and reactivity was not significant. Thus, the results partially support hypothesis 2.

Table 3.

Results of Regression Analyses Examining Daily Reactivity to Sexism as a Predictor of the Gender Typicality of Occupational Choices.

	B	B (SE)
Intercept	0.00	16.82 (9.44)
General mood level during non-sexism hourly signal	0.25	6.41 (3.04)*
Reactivity to sexism	0.32	15.02 (7.26)*
Gender	0.67	27.99 (4.54)***
Gender*Reactivity	0.08	5.19 (9.41)

Note. Gender (0 = female, 1 = male).

*p < .05, **p < .01, ***p < .001.

Follow-Up Analyses

Because Becker and Swim’s (2011) Sexist Events Checklist includes both positive and negative examples of sexism, follow-up analyses were conducted to determine if there were gender differences in specific types of sexism – as this could have implications for reactivity and occupational choices. Items were categorized based on whether the sexist event included positive stereotypes about the participant’s gender. Although 11 out of the 14 items focused on negative examples of sexism (e.g., Heard hostile beliefs about your gender), 1 item focused on positive examples (e.g., Heard traditional positive stereotypes about your gender), and 2 items could possibly include more negative, positive, or neutral examples depending on the situation (e.g., traditional treatment toward you/someone of your gender: Selected for a gender stereotypical job or assignment (or not selected for gender counter stereotypical job or assignment)). Item codings are listed in Appendix A.

Results indicated that women reported 103 negative examples of sexism and 12 positive examples, whereas men reported 66 and 13 respectively. A sum of positive, negative, and neutral examples were created for each participant, and results of an independent samples t-test indicated that there were not significant gender differences in negative, t (3518) = 1.55, p = .12, or positive examples of sexism, t (3518) = -0.30, p = .76. Men, however, reported significantly more neutral examples of sexism compared to women, t (3518) = -6.47, p < .001. Men reported 66 neutral examples of sexism whereas women reported 11 examples. However, after removing the one outlier (described in the analysis section above) – a man who reported 51 instances of complementary sexism (i.e., Heard complementary beliefs about women and men (e.g., men and women are different but complement each other)), there was no longer a significant difference in the neutral examples of sexism, t (3467) = -0.93, p = .35.

Discussion

Social Cognitive Career Theory asserts that environmental factors influence career development (Lent et al., 1994), yet there has been a lack of research on the role of daily environments, and reactivity to these environments, that may contribute to EAs’ occupational choices (Blickenstaff, 2005; Cohoon et al., 2009; Lent et al., 1994). Seemingly minor daily events, such as hearing someone express gender stereotypical beliefs about a person’s abilities, seeing someone excluded due to their gender, or experiencing unwanted flirting, may accumulate over time and have implications for the career choices of individuals. Therefore, the purpose of the current study was to examine whether daily experiences of sexism and levels of affective reactivity to sexism predicted the gender typicality of desired occupations of EA men and women in male-dominated majors.

Contrary to hypothesis 1, the current study found that sexism was not a significant predictor of desired occupation among EAs in MDMs. While the interaction between gender and reactivity was not significant in hypothesis 2, the hypothesis was partially supported in that affective reactivity to sexism significantly predicted the gender typicality of desired occupations. This means that higher levels of reactivity to sexism were associated with EAs (both men and women) desiring gender typical occupations. TMS (Lazarus & Folkman, 1984) asserts that reactivity is the product of a cognitive appraisal process of an environmental stressor (in this case, sexism). According to TMS, individuals who were more reactive likely believed the sexism was a threat to them and had fewer resources available to effectively deal with the sexism. Thus, in line with SCCT, the results show that perceptions of supportive environments are crucial to positive career development. Individuals with higher reactivity scores may have perceived their environment as less supportive, and ultimately were more likely to desire careers viewed as more practical and culturally accepted (i.e. gender typical occupations) (Lent et al., 1994, 2002). Given that reactivity, but not sexism, predicted desired occupations, the results suggest that consideration of cognitive appraisals of the daily environment (i.e., personal attributes and external environment) together may be important to consider in future research on career development.

Sexism, Reactivity, and Occupational Choices

Past research has found that women in male-dominated fields experience higher rates of sexism, harassment, exclusion, and perceive their overall workplace and/or academic environment as being more negative than their male counterparts (Barthelemy et al., 2016; Cohoon et al., 2009; DeWelde & Laursen, 2011; Erwin & Maurutto, 1998; MacLachlan, 2006; Riffle et al., 2013; Rubin et al., 2019). Based on SCCT, it would be predicted that sexism influences women attrition rates in MDMs and male-dominant occupations (Lent et al., 1994, 2002). These predictions have been found to be true in numerous research studies (Blickenstaff, 2005; Cohoon et al., 2009; Riffle et al., 2003; Torre, 2014).

Contrary to previous findings, the current study’s results found that daily sexism did not significantly predict occupational aspirations. This discrepancy may be due to a number of factors including potential methodological variation. For example, previous research has focused on traditional survey data or qualitative research examining overall sexism experienced, often from women in doctoral programs or already working in the male-dominated occupations (Cabay et al., 2018; Cohoon et al., 2009; DeWelde & Laursen, 2011; Riffle et al., 2003). Because the ESM only captured sexism experienced across a 2-week period, it is possible that it did not capture the wide range of sexist experiences that may discourage women from continuing to pursue male-dominated fields. Additionally, since these women were earlier in their career than many of the participants in previous research (the present study focused on EAs in college, whereas previous research often focused on the environments of employed women or women in graduate school), the lack of findings may also be due to the fact that the women in the present study have not been worn down by cumulative experiences of sexism. Finally, a 2-week timeframe does not allow for an examination of whether cumulative experiences of daily sexism over time – both subtle and overt – may have implications for occupational choices.

Much of the former research on sexism in relation to gender typical occupational choices has not studied affective reactivity to sexism and how this may predict gender typicality of EAs’ occupational aspirations. However, a similar article to our current study conducted by Schuster and Martiny (2017) found that when measuring anticipated positive and negative affect in stereotype activation scenarios (e.g., math viewed as typically male), female (but not male) undergraduate students anticipated the most negative affect in the stereotype activation scenario. This study also found that only when women anticipated positive affect, this mediated the effect of stereotype activation on career aspirations (Schuster & Martiny, 2017). Similar to the article by Schuster and Martiny (2017), the current study found that affective reactivity to sexism indicates preferences for gender typical occupations. However, Schuster and Martiny (2017) found gender interactions between anticipation of negative and positive affect toward stereotyping scenarios, while the current study did not find significant gender interactions. This may indicate that affective reactivity to sexism is important regarding gender typical aspirations for both women and men. The current study has extended Schuster and Martiny’s (2017) research with higher ecological validity, in that the current study asks about real-life and real-time instances of sexism and affective reactivity to sexism, versus anticipated reactions to virtual stereotype activation scenarios. This may help to explain the gender differences between the current study and Schuster and Martiny’s (2017) study, as the current study is based off real daily experiences versus perceived experiences. The current study is also one of the only studies that has looked at the importance of reactivity to sexism in relation to gender typicality of desired occupations. Therefore, this study has important implications for continuing research on male-dominated departments and experiences/perceptions of sexism.

Limitations and Future Research

While the current research found important connections between reactivity to sexism and gender typical occupational aspirations in EAs in MDMs, there are limitations to consider when pursuing future research. First, the majority of students who participated identified as white; this along with the participants all coming from the same university setting, make it necessary to obtain a more diverse sample in future research. Second, the current study focused on occupational aspirations, but we have no indication about the occupations in which participants will actually end up. In addition, the desired occupations were reported 1 day prior to the start of the ESM assessments of sexism. Although desired occupations are likely not going to change among college students over this short time frame, it does highlight that the correlational nature of the study does not allow us to examine the temporal ordering of constructs: does reactivity to sexism predict occupational choices or vice versa? Conducting a longitudinal study in the future would be beneficial in determining whether these daily experiences in MDMs during emerging adulthood have implications for occupations students obtain in the future.

Additionally, conducting research at the college level excludes populations of women who have already been selected out of MDMs at that point. ESM needs to be used on populations of children to understand daily experiences of sexism and how this relates to occupational aspirations. This is especially important based on past research findings explicating that EAs develop their occupational choices based on early interactions and socialization (Messersmith et al., 2008). Studying populations of children may inform current research on how various contextual and psychosocial factors interact to predict occupational choices in these individuals during emerging adulthood.

Finally, the current study was not designed to assess the specifics about the settings or contexts in which students were experiencing sexism. Therefore, the sexism to which students were reacting may not have been perpetuated by the students or faculty in the MDM or by people in male-dominated fields (i.e., the type of people with whom the students would be interacting in class or on the job on a regular basis). Instead, it is possible that the sexism students experienced and reacted to was not in the context of their program, not based on their desire to pursue male-typed occupations, or was perpetuated by family, friends, or strangers not in the MDM. As such, it is unclear whether the relationship between reactivity to sexism and gender-typicality of occupational aspirations is a function of salient interpersonal occupational and academic environments or of personal interpersonal environments. Future research should examine the role of the specific context (e.g., characteristics of the person who said the comment, such as gender and relationship to the person) during which sexism was experienced as it relates to the occupational aspirations of EA students in MDMs.

Implications and Conclusion

The results of this study suggest reactivity to daily sexism for both women and men EAs in MDMs predicts the gender typicality of desired occupations. Although relatively little research has assessed whether external influences such as sexism may have implications for occupational choices (Duffy & Dik, 2009), career counselors are often acutely aware that environmental factors may constrain the career-related decision-making processes of their clients. Often these factors relate to socioeconomic status (e.g., needing to provide for a family may supersede educational goals needed for a desired occupation), the results of the present study suggest that counselors should also address sexism as an additional environmental factor that may constrain occupational choices – particularly for male-dominated fields such as STEM. However, consistent with SCCT and TSM, which both take a social-cognitive approach to understand behavior, reactions to daily sexist experiences may be more important to consider than sexism by itself.

If sexism may be playing a role in the career decision-making process, counselors should likely first assess the relevance of sexism in the process. It is also important to allow an avenue for clients to be able to express frustration or anger that may occur as a result of this barrier, and to assess the extent to which these difficulties could be navigated (Duffy & Dik, 2009). The counselor may also be able to help the client identify the relative importance of both personal attributes (e.g., interests) and external factors such as sexism to help the client determine career choices that best fit their personal circumstances (Duffy & Dik, 2009).

Ideally, however, sexism would decrease in male-dominated fields so that individuals do not have to make these difficult decisions. While reducing the prevalence of sexism in MDMs should remain the ultimate goal, based on the results of the current study it may be advantageous to consider potential ways to reduce reactivity to sexism in an attempt to address the relatively high attrition rates among women in MDMs. Given the importance of resources in reactivity (Lazarus & Folkman, 1984), future research is needed to better understand environmental resources that may buffer reactivity to sexism. For instance, given literature emphasizing the importance of role models for underrepresented groups in STEM (Drury et al., 2011), future research could examine whether the presence of women role models may help to reduce women’s reactivity to daily sexist experiences.

Footnotes

Acknowledgments

The author thanks Rahissa Winningham, Adrianna Caballero, Marcy Beutlich, Kendall Smith, Krista Kranz, and Charlie Jackson for their help with survey testing and data collection, and Adrianna Caballero and Danka Maric for their coding of occupations.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The present study was funded by Ball State University’s Aspire Internal Grant Program to Katie M. Lawson, Principal Investigator

ORCID iD

Katie M. Lawson

Appendix

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